Using R and Python for Common SAS Functions - Data Science Blog by Domino

SAS is the recognized incumbent in the analytics, statistics and data science tool space. As the software celebrates its 50th birthday this year, it has evolved into a broad suite of tools and approaches that tries to do everything. From basic inference to the most complex clinical trials, SAS is trying to provide a framework for everyone. Even with 50 years of code (or perhaps because of 50 years of code), there are some areas where SAS may be falling behind. People interested in data science have been watching open source statistical environments develop as alternate solutions for full cycle data science programs. Over the last 5 years, two contenders, R and Python, have proven themselves to be capable and worthwhile investments professionally and organizationally.